Advanced Search
MyIDEAS: Login to save this paper or follow this series

Methods for estimating a conditional distribution function

Contents:

Author Info

  • Rodney C Wolff
  • Peter Hall
  • Qiwei Yao

    (School of Economics and Finance, Queensland University of Technology)

Registered author(s):

    Abstract

    Motivated by the problem of setting prediction intervals in time series analysis, we suggest two new methods for conditional distribution estimation. The first method is based on locally fitting a logistic model and is in the spirit of recent work on locally parametric techniques in density estimation. It produces distribution estimators that may be of arbitrarily high order but nevertheless always lie between 0 and 1. The second method involves an adjusted form of the Nadaraya--Watson estimator. It preserves the bias and variance properties of a class of second-order estimators introduced by Yu and Jones but has the added advantage of always being a distribution itself. Our methods also have application outside the time series setting; for example, to quantile estimation for independent data. This problem motivated the work of Yu and Jones.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://eprints.qut.edu.au/5939/
    Download Restriction: no

    Bibliographic Info

    Paper provided by School of Economics and Finance, Queensland University of Technology in its series School of Economics and Finance Discussion Papers and Working Papers Series with number 208l.

    as in new window
    Length:
    Date of creation: 15 Jun 2006
    Date of revision:
    Handle: RePEc:qut:dpaper:208l

    Contact details of provider:
    Postal: GPO Box 2434, BRISBANE QLD 4001
    Email:
    Web page: http://www.bus.qut.edu.au/faculty/economics/
    More information through EDIRC

    Related research

    Keywords: Absolutely regular; bandwidth; biased bootstrap; conditional distribution; kernel methods; local linear methods; local logistic methods; Nadaraya-Watson estimator; prediction; quantile estimation; time series analysis; weighted bootstrap;

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Inference for Integrated Volatility," Departmental Working Papers 200616, Rutgers University, Department of Economics.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:qut:dpaper:208l. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Angela Fletcher).

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.